Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method

Deng, Yongbo; Korvink, Jan G.

doi:10.1098/rspa.2015.0835

Cited by 36 publications

(16 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, progress has been made with both forward design methods, such as transformation optics [97][98][99][100][101] and scattering cancellation [102], and inverse design approaches [103]. Genetic algorithms are usually adopted for optimizing a multilayer particle or cylinder to achieve omnidirectional scattering reduction [104,105], while topology optimization is more practically associated with designing bidirectional cloaks or resonators that can be realized by a low-index material [106][107][108][109][110][111][112], although in theory it can work for any imaginable objective function [106,113]. Figure 5 summarizes a few examples based on topology optimization.…”

Section: Nanophotonic Design Based On Optimization Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale

2019

View full text Add to dashboard Cite

Nanophotonics has been an active research field over the past two decades, triggered by the rising interests in exploring new physics and technologies with light at the nanoscale. As the demands of performance and integration level keep increasing, the design and optimization of nanophotonic devices become computationally expensive and time-inefficient. Advanced computational methods and artificial intelligence, especially its subfield of machine learning, have led to revolutionary development in many applications, such as web searches, computer vision, and speech/image recognition. The complex models and algorithms help to exploit the enormous parameter space in a highly efficient way. In this review, we summarize the recent advances on the emerging field where nanophotonics and machine learning blend. We provide an overview of different computational methods, with the focus on deep learning, for the nanophotonic inverse design. The implementation of deep neural networks with photonic platforms is also discussed.This review aims at sketching an illustration of the nanophotonic design with machine learning and giving a perspective on the future tasks.

show abstract

Section: Nanophotonic Design Based On Optimization Techniquesmentioning

confidence: 99%

“…[ 108 ] with permission of American Institute of Physics (AIP); (D) is reprinted from Ref. [ 110 ] with permission.…”

Section: Figurementioning

confidence: 99%

Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale

2019

View full text Add to dashboard Cite

show abstract

“…A typical mesh consisting of 4932 total mesh vertices and 25748 tetrahedra elements in the entire domain.was selected for numerial investigations. The wave equation for the propagation of electric field "E" by solving the Maxwell equations is given as [53], The wavenumber k 0 for free space is defined as [54], The electric displacement field model was selected for the refractive index, which was calculated using the permittivity and permeability values of the materials. The average values of relative permittivity for S 0 , S B , S Zn, and S Bi presented in Table 2 have been calculated using the measured values from VNA.…”

Section: Numerical Simulationmentioning

confidence: 99%

Absorption of electromagnetic waves in sandstone saturated with brine and nanofluids for application in enhanced oil recovery

Ali

Soleimani

Yahya

et al. 2020

Journal of Taibah University for Science

View full text Add to dashboard Cite

In this study, scattering parameters of sandstone saturated with brine and nanofluids are evaluated experimentally and numerically for the application in enhanced oil recovery (EOR). Zinc Oxide (ZnO) and Bismuth ferrite BiFeO 3 (BFO) nanoparticles were synthesized via facile sol-gel method followed by nanofluid preparation. Sandstone samples were saturated with brine and nanofluids for 48 h. Electromagnetic properties of the saturated sandstones were measured experimentally using the vector network analyzer, and the scattering parameters of the samples were studied numerically by finite element method. BFO displayed higher permeability value of 1.52 and 1.30, as well as superior dielectric permittivity value 11.55 and 6.59 for real and imaginary parts, respectively. In addition, the sandstone saturated with BFO showed an impressive reflection loss (RL) value of −9.77 dB at high frequency. Conclusively, BiFeO 3 nanofluids showed the best potential to enhance oil recovery which can be accredited to the superior electromagnetic properties of BFO. ARTICLE HISTORY

show abstract

“…In a sense, however, this design freedom has not been utilized to its full potential, with topology optimization being primarily used to design planar devices, [17][18][19][20][21] with only few examples of fully three-dimensional geometries. 22,23 This is of course not without good reasons, and chiefly among these are restrictions imposed by available manufacturing techniques. However, recent advancements in additive manufacturing techniques such as 3D laser nanolithography 24,25 have put fabrication of fully three-dimensional micro-structures well within reach.…”

Section: Introductionmentioning

confidence: 99%

Inverse Design of Nanophotonic Devices with Structural Integrity

Augenstein

Rockstuhl

2020

ACS Photonics

View full text Add to dashboard Cite

Computational inverse design has been a driving force behind the development of compact and highly efficient nanophotonic devices. However, due to fabrication constraints, devices have so far mostly been restricted to planar geometries. With recent developments, additive manufacturing techniques are poised to open up a vast design space for free-form nanophotonic devices, bringing with them a new set of inverse new possibilities for photonic device design and may lead to the development of novel photonic devices for additive manufacturing.

show abstract

Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method

Cited by 36 publications

References 59 publications

Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale

Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale

Absorption of electromagnetic waves in sandstone saturated with brine and nanofluids for application in enhanced oil recovery

Inverse Design of Nanophotonic Devices with Structural Integrity

Contact Info

Product

Resources

About